Anglia Ruskin Research Online (ARRO)
Browse

File(s) under permanent embargo

A Conceptual Model for Data-Driven Threat Analysis for Enhancing Cyber Security

conference contribution
posted on 2023-09-04, 10:49 authored by Mohammed KS Alwaheidi, Shareeful Islam, Spyridon Papastergiou
Technology has become increasingly adopted by businesses for achieving overall objectives. Systems within these technologies generate a huge amount of data. It is necessary to identify the data and undertake appropriate controls to protect the data from any potential threats. Data, in general, is different types, such as operational and business which have different costs and impact on the overall business continuity. Threat analysis needs to consider various data types and associated weaknesses related to an organisational context's systems and applications. There are numerous threat models available, but there is a lack of focus on analysing and prioritizing threats relating to the data. This paper presents a data-driven approach for threat analysis and a conceptual model. The model includes several concepts, i.e., actor, infrastructure, data and weakness, to analyse the data and threats from three phases management, control and business. Finally, a running example is used to demonstrate the applicability of the work.

History

Page range

365-374

ISSN

2194-5365

Publisher

Springer International Publishing

ISBN

9783031140532

Conference proceeding

Advances in Intelligent Systems and Computing

Name of event

The International Conference on Innovations in Computing Research

File version

  • Accepted version

Language

  • eng

Legacy posted date

2022-09-06

Legacy creation date

2022-09-06

Legacy Faculty/School/Department

Faculty of Science & Engineering

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC